Abstract:Online examination system is a web-based examination system where examinations are given online. either through the internet or intranet using computer system. The main goal of this online examination system is to effectively evaluate the student thoroughly through a totally automated system that not only reduce the required time but also obtain fast and accurate results.

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This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT), (median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Laplace has recorded a better accuracy. Our experimental evaluation on real data from the Kadhimiya teaching hospital shows that the proposed CUHF is a better method when compared to the accuracy of the other integrated filters.

Image encryption is among the most active solutions to protect confidential pictorial information. However, to design a strong image encryption algorithm with no recognizable pattern, the researchers in this field have to enrich the confusion and diffusion properties. This study proposes an efficient hybrid system that combines two techniques. First, we propose a modified version of Rubik's Cube technique for scrambling colored image pixels to achieve fast confusion. This technique not only scrambles the position of image pixels but also scrambles the color channels. Then, dynamic DNA encoding algorithm is used to encrypt the pixel's values. DNA encoding rules are used in conjunction with a secret key. We propose to select the DNA rules dynamically to enhance the security level. Five fidelity metrics are employed to assess the capability of this system. These are PSNR, SSIM, NPCR, Entropy, and CCA. The results indicate that the proposed system enhances the general security requirements with enriched confusion and diffusion properties of the encrypted image.